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Magnetic Resonance Imaging

The group does research in machine learning applications in magnetic resonance imaging (MRI) of the human brain. One application is the spectroscopic MRI, which aims to detect metabolite levels in the brain using spectral methods, which is useful for the characterization of certain mental diseases.

In this application it is necessary to reduce the influence of the lipid spectrum around the brain to prevent this blurring the metabolite spectrum. This is achieved by positioning field bands on lipids to increase its resonance frequency and thus move its spectrum away from the metabolites. The placement process is manual, and only good results in two dimensions are achieved. besides, it is very tedious and time consuming in three dimensions, which should be placed up to 16 bands around the brain.

G2PI, in collaboration with the MIND Imaging Center (USA) and other centers, developed a technique to fully automatically and quick positioning between 6 and 16 bands of magnetic field, achieving high efficiency through an objective quality measure. We developed a graphical application in Matlab (left image) and carried out experiments in vivo MRIs in three dimensions, something that had not been achieved so far. The results and proposed algorithms can be seen in the papers of Martinez et al, 2010 and Yung et al., 2011, both in Magnetic Resonance in Medicine.